Purpose

– The purpose of this paper is to analyze and compare the performance of several different UAV trajectory tracking algorithms in normal and abnormal flight conditions to investigate the fault‐tolerant capabilities of a novel immunity‐based adaptive mechanism.

Design/methodology/approach

– The evaluation of these algorithms is performed using the West Virginia University (WVU) UAV simulation environment. Three types of fixed‐parameter algorithms are considered as well as their adaptive versions obtained by adding an immunity‐based mechanism. The types of control laws investigated are: position proportional, integral, and derivative control, outer‐loop nonlinear dynamic inversion (NLDI), and extended NLDI. Actuator failures on the three channels and increased turbulence conditions are considered for several different flight paths. Specific and global performance metrics are defined based on trajectory tracking errors and control surface activity.

Findings

– The performance of all of the adaptive controllers proves to be better than their fixed parameter counterparts during the presence of a failure in all cases considered.

Research limitations/implications

– The immunity inspired adaptation mechanism has promising potential to enhance the fault‐tolerant capabilities of autonomous flight control algorithms and the extension of its use at all levels within the control laws considered and in conjunction with other control architectures is worth investigating.

Practical implications

– The WVU UAV simulation environment has been proved to be a valuable tool for autonomous flight algorithm development, testing, and evaluation in normal and abnormal flight conditions.

Originality/value

– A novel adaptation mechanism is investigated for UAV control algorithms with fault‐tolerant capabilities. The issue of fault tolerance of UAV control laws has only been addressed in a limited manner in the literature, although it becomes critical in the context of imminent integration of UAVs within the commercial airspace.